{"id":"W4224211344","doi":"10.3390/app12094181","title":"EEG Oscillatory Power and Complexity for Epileptic Seizure Detection","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université TÉLUQ","funders":"Fonds de recherche du Québec – Nature et technologies; Canada Research Chairs","keywords":"Electroencephalography; Epileptic seizure; Artificial intelligence; Pattern recognition (psychology); Computer science; SIGNAL (programming language); Decision tree; Random forest; Speech recognition; Psychology; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001111984,0.000523605,0.0005271778,0.001962403,0.0002097469,0.0007676248,0.0002209769,0.0003399612,0.001393758],"category_scores_gemma":[0.005840545,0.0001206577,0.0003300306,0.001246876,0.0002184003,0.0007740588,0.000414171,0.0003466949,0.0005124179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002022453,"about_ca_system_score_gemma":0.0003083498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007089366,"about_ca_topic_score_gemma":0.001143825,"domain_scores_codex":[0.9994497,0.0001692779,0.00005505721,0.00007784507,0.0002191505,0.00002910975],"domain_scores_gemma":[0.9976467,0.001448645,0.0003354762,0.0001433212,0.0003276196,0.00009818291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001424575,0.000450927,0.1983544,0.0003740269,0.0002327191,0.0003355821,0.0001959957,0.02423121,0.06546364,0.001693797,0.001995575,0.7052476],"study_design_scores_gemma":[0.00007278084,0.001606667,0.5774773,0.0001489699,0.0002774408,0.001362258,0.0002530536,0.3922201,0.01994834,0.003339668,0.003198054,0.00009531536],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8171322,0.003699199,0.1716888,0.000392252,0.00007595762,0.0002001717,0.000925704,0.0006356176,0.005249983],"genre_scores_gemma":[0.9623295,0.0008494491,0.03571577,0.00003720264,0.0000717975,0.00005708228,0.0004109676,0.00002363238,0.0005045872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001962403,"threshold_uncertainty_score":0.005880833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05293289746242903,"score_gpt":0.2780242455106438,"score_spread":0.2250913480482147,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}